This paper is concerned with the mitigation of simple contrast loss due to added lightness in an image. This added lightness has been referred to as "airlight" in the literature since it is often caused by optical scattering due to fog or mist. A statistical model for scene content is formulated that gives a way of detecting the presence of airlight in an arbitrary image. An algorithm is described for estimating the level of this airlight given the assumption that it is constant throughout the image. This algorithm is based on finding the minimum of a global cost function and is applicable to both monochrome and color images. The method is robust and insensitive to scaling. Once an estimate of airlight is achieved, then image correction is straightforward. The performance of the algorithm is explored using the Monte Carlo simulation with synthetic images under different statistical assumptions. Several examples of before and after color images are given. Results with real video data obtained in poor visibility conditions indicate frame-to-frame consistency of better than 1% of maximum level.